中国有色金属学报(英文版)
Transactions of Nonferrous Metals Society of China
| Vol. 23 No. 3 March 2013 |
（1. National Key Laboratory for Precision Hot Processing of Metals,
Harbin Institute of Technology, Harbin 150001, China;
School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China;
3. Beijing Hangxing Machine Manufacturing Company, Beijing 100013, China;
4. Physical Test Centre, Shenyang Aircraft Corporation, Shenyang 110034, China）
Abstract:The workpieces of A357 alloy were routinely heat treated to the T6 state in order to gain an adequate mechanical property. The mechanical properties of these workpieces depend mainly on solid-solution temperature, solid-solution time, artificial aging temperature and artificial aging time. An artificial neural network (ANN) model with a back-propagation (BP) algorithm was used to predict mechanical properties of A357 alloy, and the effects of heat treatment processes on mechanical behavior of this alloy were studied. The results show that this BP model is able to predict the mechanical properties with a high accuracy. This model was used to reflect the influence of heat treatments on the mechanical properties of A357 alloy. Isograms of ultimate tensile strength and elongation were drawn in the same picture, which are very helpful to understand the relationship among aging parameters, ultimate tensile strength and elongation.
Key words: A357 alloy; mechanical properties; artificial neural network; heat treatment parameters
